Canadian Journal of Fisheries and Aquatic Sciences

Philippine freshwater ecosystems are considered one of the most diverse ecosystems harboring numerous fish species. However, in the Philippines, these ecosystems are threatened by invasive species that potentially disrupt ecological balance. In this study, we focused on the vermiculated sailfin catfish Pterygoplichthys disjunctivus, an invasive aquarium species reported in several Philippine aquatic ecosystems. Despite its documented spread, its potential range under a rapidly changing climate remains poorly understood for the country. Hence, in this study, we utilized the MaxEnt model to predict its near-current and future habitat suitability in the Philippines. Using 11 reported occurrences, our model showed high predictive accuracy (AUC = 0.882{+/-} .034, TSS = 0.7394 {+/-} 0.154, SEDI = 0.971 {+/-} 0.019). Across the current and future scenarios, slope was the primary contributor (78.7% - 81.3%), followed by BIO 10 or the mean temperature of the warmest quarter(18% - 27.8%), and flow accumulation (0% - 5.2%). However, for the SSP126 scenario, BIO10 is projected to triple by 2050 (18 - 48%). Current projections identify high-risk regions, particularly central Luzon (Laguna de Bay and Lake Taal), the Cagayan River Valley, and portions of eastern Mindanao (Agusan Marsh and Lake Mainit). Sankey transition analysis confirms a high habitat stability rate (>73%) for high-suitability pixels in both SSPs, indicating persistent invasion risk. Overall, our study provides a framework for invasive species management and contributes to the conservation of Philippine aquatic ecosystems.

Guinea worm disease eradication efforts may benefit from environmental surveillance methods capable of detecting infected copepod intermediate hosts in aquatic habitats. We developed a three-dimensional, spatially explicit agent-based model to examine how ecological processes influence detection probability for a hypothetical water sampling method. The results show that surveillance sensitivity is shaped by the combined effects of larval diffusion, copepod density, and pond size, with interactions among these factors producing nonlinear relationships. Detection, in our model, was concentrated within a relatively restricted period after larvae matured to the infective stage and before dispersal and mortality reduced presence, indicating a limited spatiotemporal window for effective sampling. Surveillance performance peaked under intermediate dispersal regimes that generated sufficient spatial overlap between larvae and intermediate hosts, while both limited dispersal and excessive diffusion reduced detection by constraining encounters or diluting larval concentrations. Increasing habitat size reduced detection by diluting larval concentrations, but the magnitude of this effect depended on copepod density and dispersal dynamics, producing nonlinear and threshold responses rather than simple scaling with pond volume. Spatial and temporal patterns of detection shifted as larvae dispersed, with the most favorable detection periods occurring when both larval abundance and intermediate host encounters were elevated. These findings indicate that surveillance can be guided by local ecological conditions. When the timing of larval introduction is uncertain, effective surveillance requires repeated sampling over time to capture transient windows of detectability and the sampling will be less effective in very stagnant and highly mixed waterbodies. Overall, this study demonstrates how mechanistic modeling can support the design and interpretation of environmental surveillance strategies for Guinea worm eradication programs. Author summaryGuinea worm disease is close to eradication but confirming that transmission has fully stopped remains difficult because detecting infectious larvae in water is challenging. Transmission depends on freshwater copepods that become infected after ingesting Guinea worm larvae. These copepods are short-lived and unevenly distributed within ponds, and infected individuals may die before larvae reach the infective stage. As a result, environmental detection is inherently uncertain. We developed a three-dimensional agent-based model to simulate larval dispersal, copepod infection, and water sampling in a pond environment. The model shows that detection is constrained to a brief period when mature larvae and copepods overlap in space and time, and that this window depends strongly on local ecological conditions such as larval dispersal, copepod density, and pond size. Because infected copepods can be present outside these narrow detection windows, negative water samples do not necessarily indicate absence of transmission, highlighting the need for repeated, spatially targeted surveillance during the final stages of eradication.

Non-compliance with regulations threatens the sustainability of fisheries worldwide. Understanding the interconnected feedbacks of this complex social-ecological problem is key for sustainability but rarely integrated into fisheries management. We provide an adaptive stochastic modelling framework that integrates economic, social behavior, and ecological aspects of the Chilean kelp fishery, which plays a critical economic and ecological role in coastal social-ecological ecosystem. High levels of non-compliance is threatening sustainability, fishers well-being, and ecosystem health. Our model considers inherent environmental uncertainties and enables the assessment of different harvesting and compliance scenarios and the role of market-based economic incentives in reducing non-compliance. Results show that, unlike the sustainability obtained under an idealized full-compliance scenario, under dynamic compliance the social, economic, and ecological feedbacks leads to system collapse. Importantly, price premiums can promote compliance and sustainability, but the probability of collapse, albeit small, still exist. Our generalizable stochastic modeling framework evidenced that accounting for inherent uncertainty in natural resource management is key to designing interventions for sustainability.

O_LIEnvironmental DNA (eDNA) metabarcoding is an emerging tool for biodiversity assessment in freshwater systems, offering high-resolution insights into community composition. Here, we apply eDNA metabarcoding to evaluate the ecological impacts of Eurasian beaver (Castor fiber) activity within a seminatural enclosure in the Scottish Highlands. C_LIO_LIWe collected seasonal water samples from nine sites, six influenced by beaver dams and three control sites with no evidence of beaver engineering, across a 40-hectare enclosure. Samples were analysed for vertebrate and macroinvertebrate diversity using established 12S and COI markers. C_LIO_LIVertebrate alpha diversity did not differ significantly between beaver and control sites, likely reflecting the small spatial scale and low species richness of upland Scottish streams. However, community composition differed significantly between treatments, especially for fish (PERMANOVA, R2 = 0.55, P < 0.001), with beaver-influenced sites dominated by three-spined stickleback and control sites by brown trout. Macroinvertebrate communities showed a 78% increase in gamma diversity in beaver-modified habitats relative to controls. Species composition varied strongly with beaver presence (PERMANOVA, R2 = 0.29, P < 0.001), likely due to the creation of lentic-lotic mosaics and associated microhabitat diversity. Seasonal variation was significant in both taxonomic groups, with the lowest species richness and highest community dispersion observed in summer, probably reflecting hydrological and temperature-driven dynamics in eDNA production and transport. C_LIO_LIOur findings reinforce previous evidence that beaver dam-building activity enhances beta diversity in headwater systems. Additionally, we demonstrate that eDNA metabarcoding is a sensitive method for detecting spatial patterns in freshwater biodiversity associated with these activities at scales ranging from tens to hundreds of meters. These approaches could inform future monitoring strategies aligned with landscape-scale beaver management and reintroductions. C_LI

Seafood nutrients from global fisheries are of increasing importance for research and policy in food security and nutrition. As the chemical composition of fish is determined by what they eat, their energetic demands, and the environment in which they live, nutrient content reflects aspects of physiology and life history, ecological and environmental traits, as well as evolutionary history. Here we present data from Bayesian model estimates of 12 key nutrients (calcium, iron, phosphorus, magnesium, selenium, zinc, vitamin A, vitamin B9, vitamin B12, vitamin D, omega-3 fatty acids, and protein) in wild fish, using a database of reported nutrient content for freshwater and marine species. We then predict the nutrient content of 5588 fish species with traits available from FishBase. We compare our previous model using traits alone with a new model of both traits and phylogeny, and present the data, code, and predictions for models coded in PyMC. These models and predictions, made freely available through FishBase, can be used to explore the historical, current, and future nutrient content of fisheries catch.

There is an urgent need to gather data on harvest rates of waterbirds in Europe to assess the sustainability of hunting. Estimates of total waterbird harvest in the United Kingdom (UK) and the relative harvest of different huntable species come from two separate surveys, the Value of Shooting (PACEC 2014) and National Gamebag Census (NGC, Aebischer 2019), and these have been recently used to explore the likelihood of unsustainable harvests of wild waterbirds by UK hunters (Ellis and Cameron 2022; Madden et al., 2025). The reliability of these sustainability estimates depends on how representative the original surveys are of hunter behaviour and success. There are also 1-3 million released game-farm mallard (Anas platyrhynchos) that takes up considerable and unquantified proportions of the UK waterbird harvest. Here we explore uncertainties in the UK winter harvest of wild waterfowl by comparing estimates from the NGC dataset with those from the Crown Estate coastal hunting clubs, and a novel approach using analysis of social-media images (2019/20 to 2023/24). We explore the difference in species-specific harvest with and without the uncertainties in the number of released mallard and the total number of duck harvested in the UK. Waterbird harvest estimates differ markedly depending on the input dataset and whether released mallard are included in the analysis. Confidence intervals of each estimate are inflated by uncertainties in the number of released game-farm mallard contributing to, and the size of that national bag. Estimates extrapolated from social media suggest the national harvest of several species may be considerably larger than the corresponding NGC estimates (e.g. Teal *2.07 and gadwall *11.2), while mallard harvests away from formal shoots represented by NGC are significantly lower (*0.71). Excluding released mallard reduces the statistical estimate of total wild duck harvest by 56-63%, which would have biologically significant effects if realised.

AO_SCPLOWBSTRACTC_SCPLOWClose-Kin Mark-Recapture (CKMR) is a statistical framework for estimating demographic parameters of wild populations. Instead of recapturing individuals, it relies on the identification of closely-related pairs such as parents and offspring, or siblings. By measuring how often such close-kin are "recaptured" among sampled animals (whether alive or dead), scientists can estimate demographic parameters such as census size, mortality rates, and connectivity. CKMR is starting to change fisheries and wildlife management by giving more reliable demographic information, even for many species that resist conventional approaches. Here we introduce the kinference R package, which provides a set of tools for finding close-kin pairs among thousands of samples each genotyped at thousands of SNPs, and for associated quality control. The CKMR context implies different requirements and assumptions to many other kinship programs. In particular, kinference accounts empirically for linkage without requiring a genome assembly, is able to estimate and control false-negative and false-positive probabilities, and can cope with null alleles. The package has been developed and used in numerous CKMR projects since 2017. This paper documents the assumptions, statistical algorithms, and intended workflow for kinference.

Pollution of aquatic environments poses an increasingly severe threat to ecosystems worldwide, and understanding its molecular consequences for aquatic organisms requires extensive research and the development of advanced analytical tools. Phosphoproteomics can be particularly valuable for this purpose, as shifts in phosphorylation states can serve as early molecular indicators of toxic exposure. The cladoceran Daphnia is a keystone species in aquatic ecosystems, linking lower and higher trophic levels, and is therefore widely used as a model organism in ecotoxicology to study biological consequences of pollution. Here, we present a simple and effective strategy to analyse the phosphoproteome of Daphnia magna, a commonly used Daphnia species in ecotoxicology. Following TiO2-based phosphopeptide enrichment and LC-MS/MS analysis, we identified a comprehensive dataset of 3,532 phosphorylation sites across 1,329 phosphoproteins. These proteins were especially involved in signaling pathways and cellular structure and the vast majority have not yet been demonstrated in other Daphnia species. In conclusion, our results demonstrate that a straightforward phosphoproteomic LC-MS/MS workflow in D. magna can serve as a powerful tool for investigating adverse molecular effects caused by anthropogenic pollution, such as microplastics or pharmaceuticals. Statement of significanceThe dataset presented here demonstrates the feasibility of a simple yet effective strategy to perform phosphoprotemics in Daphnia magna, and it will be particularly valuable for future ecotoxicoproteomics research using this model organism.

The prevalence of nitrogen limitation and nitrogen-phosphorus co-limitation (henceforth referred to as nitrogen-related limitation) in Norwegian lakes and their relationships with atmospheric nitrogen deposition, climate, dissolved organic matter (DOM), and catchment characteristics were assessed across space and time. Routine monitoring data from 1,529 lakes in the national Vannmiljo database were analyzed for two multi-year periods (1995-2009 and 2010-2025). Limitation was inferred using the molar NO--N/TP ratio as an indicator of dissolved inorganic nitrogen availability. Nitrogen-related limitation was widespread in both periods and exhibited strong regional structure, with highest prevalence in northern regions and lowest prevalence in southwestern Norway. Overall prevalence increased from 31% to 38% between periods, with significant increases in western regions. Regional-scale models identified climate, forest cover, DOM, agriculture, and atmospheric nitrogen deposition as predictors of limitation probability, whereas study period per se and bog/peatland cover were not significant. At the local scale, atmospheric nitrogen deposition and DOM were the only consistent predictors, with substantially lower explanatory power than at the regional scale. These results indicate that large-scale environmental gradients play a major role in shaping nutrient stoichiometry in Norwegian lakes. Because the monitoring dataset primarily represents lakes affected by human activities, the findings are particularly relevant for water management. The widespread occurrence of nitrogen-related limitation suggests that nitrogen availability may influence phytoplankton growth in many systems and that dual-nutrient management strategies addressing both nitrogen and phosphorus may be required in many regions.

Designing effective spatial management for chondrichthyans (sharks, skates, rays and chimaeras) requires incorporating critical areas, sites essential for population maintenance, such as reproductive and feeding areas. Yet most area-based measures have been developed without consideration of chondrichthyan habitat use. The Important Shark and Ray Area (ISRA) initiative has been pivotal in designating priority areas through a rigorous, consultative process. To complement this, our study offers researchers a testable definition for generating robust evidence to strengthen future critical area delineations and related management decisions. We define critical areas using three criteria: 1) relative frequency of use, (2) extended within-year occupancy and (3) repeated use across years. This framework enables objective comparison among candidate sites and is generalisable across different critical area types. The definition builds upon established early-life-stage habitat concepts and applies these to broader life-history functions. The utility of this framework is then demonstrated through a systematic review of contemporary peer-reviewed literature of critical chondrichthyan areas in the European Atlantic. The review highlighted 62 critical areas with Strong evidence and 41 areas of Moderate strength evidence, which informed the European Atlantic ISRA selection process. Research effort was concentrated in inshore areas, particularly around the British Isles and Portugal, with biases towards large, threatened and commercially valuable species, whilst chimaeras were notably underrepresented. Early-life stage areas were most frequently identified, whereas resting areas were rarely documented. Evidence patterns and biases are examined in the context of evolving critical area concepts to advance their development and improve the quality and breadth of future research. By outlining a testable definition, identifying key knowledge gaps, and proposing research and reporting guidelines, this work enhances the consistency, comparability, and spatial coverage of future chondrichthyan habitat research to support its application to conservation planning.

Elucidating how habitat degradation facilitates extinction is critical for effective conservation efforts. Here, we propose integrating physiologically-structured population models into stochastic population viability analyses to assess how differing consequences of habitat degradation interact to drive extinction dynamics in a focal population. Using the isolated spectacled caiman Caiman crocodilus population/ecomorph from the Apaporis River as a case study, we find that threatening the resource base, which individuals increasingly rely upon, to outgrow vulnerable size ranges and mature accelerates extinction. We also found that when habitat degradation impacts both the primary adult and juvenile resource bases, this can have marked synergistic effects on threatening population viability. By contrast, destroying nesting sites has only a small effect on accelerating the impact of deteriorating prey availability. Through integrating community-level feedback between habitat degradation/change and population dynamics/structure, our approach provides a comparative framework for assessing the relative importance of distinct mechanisms through which habitat degradation ultimately drives extinction risk.

Regulation of water permeability in the collecting duct is important for osmoregulatory acclimation in teleost fish. In hyperosmotic environments such as seawater (SW), the teleost kidney functions as a site of divalent ion excretion. The collecting ducts reabsorb Na+, Cl-, and water, thereby reducing urine volume and producing small amounts of isotonic urine with high concentrations of divalent ions. In hypoosmotic environments such as freshwater (FW) or low-salinity brackish water (BW), the kidney produces large volumes of hypotonic urine and serves as a site of water excretion; under these conditions, the collecting ducts reabsorb Na+ and Cl- but not water. To identify aquaporins (Aqps) involved in regulating water permeability in the collecting ducts of teleosts, we analyzed renal Aqp expression in a euryhaline marine fish, the Japanese pufferfish (Takifugu rubripes), which possesses 16 Aqp genes in its genome, seven of which (Aqp1aa, 1ab, 3a, 4a, 7, 8bb, and 11a) are expressed in the kidney. Quantitative RT-PCR analysis showed that Aqp1aa and Aqp4a were highly expressed in collecting duct tissues, and that Aqp1aa expression was markedly reduced in fish acclimated to BW. Immunohistochemistry revealed apical localization of Aqp1aa and basolateral localization of Aqp4 in collecting duct cells, with apical Aqp1aa downregulated in BW. These results suggest that Aqp1aa and Aqp4 mediate water reabsorption in SW and that downregulation of Aqp1aa contributes to hypotonic urine production in BW. NEW & NOTEWORTHYRegulation of water permeability in the collecting duct is important for osmoregulation in teleost fish. Expression analyses of aquaporins (Aqps) in the marine pufferfish Takifugu rubripes showed that Aqp1aa and Aqp4a are highly expressed in the collecting duct and localized to the apical and basolateral membranes, respectively. Renal Aqp1aa expression was markedly reduced in fish acclimated to hypoosmotic brackish water. These results indicate that collecting duct water permeability is regulated by Aqp1aa expression.

Many marine invertebrates are characterized by broad and highly plastic thermal limits, though the dynamic molecular mechanisms that enable extended thermal acclimation remain poorly understood. A classic example is the green crab (Carcinus maenas), which is a prolific and damaging non-indigenous species. Using a 22-day thermal exposure to cold (5{degrees}C), ambient (13{degrees}C), or warm (30{degrees}C) temperatures, we characterized plastic shifts in C. maenas performance using respirometry and time-to-right. We then used untargeted metabolomics and lipidomics analysis of heart tissues from days 4 and 22 to identify the molecular mechanisms underpinning plastic responses over time. Crabs at 30{degrees}C exhibited higher oxygen consumption rates than counterparts at 5{degrees}C. Interestingly, oxygen consumption rate increased over time at both temperatures, indicating thermal plasticity of aerobic respiration. Temperature-dependent metabolic reprogramming was employed by crabs to sustain aerobic respiration across temperature. Catabolism of branched-chain amino acids was important for energy production at elevated temperatures, while catabolism of arginine may have sustained the minimal energy needs of crabs exhibiting metabolic depression at cold temperatures. Righting response was positively correlated with temperature, and did not exhibit any changes over time. Lipidome remodeling consistent with homeoviscous adaptation could have enabled motor activity across temperature. Higher abundances of saturated and monounsaturated lipids likely provided structural integrity to cell membranes at 30{degrees}C, while lower abundances of these compounds may have enabled membrane fluidity at 5{degrees}C. Our work demonstrates the importance of ongoing molecular reprogramming in long-term acclimation, even when whole-animal physiology remains relatively stable. Summary StatementThis study demonstrates how the highly invasive green crab regulates metabolite and lipid pathways over time to maintain physiological performance across different temperatures.

Reef manta rays (Mobula alfredi) are threatened by fishing and other anthropogenic threats. Which, when coupled with conservative life history traits, have made this species vulnerable to extinction. Spatiotemporal ecological knowledge, such as site fidelity and visitation patterns to key aggregation sites, are imperative for effective conservation management of M. alfredi. A novel method of environmental sensing, remote underwater photo systems (RUPs), was employed to understand drivers of M. alfredi habitat use and resighting patterns. RUPs were deployed at four cleaning sites around Laamu Atoll, Maldives. Between March 2021 and May 2023, 455,458 photos were analysed. Generalised linear models revealed increases in M. alfredi presence in response to high chlorophyll-a concentrations, low illumination moon states, the Southwest Monsoon, and in the morning, while human presence had no effect. Branchial spot patterns allowed for 81 M. alfredi individuals to be identified, from 629 sightings, representing 51.59% of Laamu Atolls previously identified population (n = 157). Cleaning stations are visited more intensively during periods of increased productivity of the Southwest Monsoon, likely in response to greater foraging opportunities near the study areas. Additionally, moon state, used as a proxy for tidal strength, was associated with increased visitation during new moon periods, suggesting that weaker tidal states may facilitate presence. These data support integrating RUPs with observational surveys to improve inferences about habitat use and our understanding of cleaning sites frequented by M. alfredi. This study aims to inform the implementation of Laamu Atolls first marine protected area management plan.

Explainable machine learning (ML) methods are gaining increasing attention in environmental and ecological research for their ability to reveal relationships between environmental drivers and population dynamics. However, there remain questions on the reliability of these tools, especially given recent research shows that these explanations can be highly sensitive to model architecture. In ecology, it is typical to use a single ML model, and a comparative evaluation of sensitivity of explainability for different ML approaches is overlooked. In this paper, we develop a novel framework that quantifies explanation consistency between multiple ML model architectures. This framework provides a discrepancy measure for each model prediction, with high discrepancy indicating substantive explanation disagreement across models and low discrepancy indicating strong consensus in explanations across models. We then demonstrate that low explanation discrepancy aligns well with ground truth mechanism. Furthermore, high explanation discrepancy provide a mechanism to identify areas for model refinement and further investigation by domain experts. We do this by using a simulation study based on synthetic coral cover data that incorporate spatio-temporal variability driven by known disturbance effects. Our method provides a quantitative approach to assess the sensitivity of explainable ML in the absence of ground truth. As a result, this enhances the utility of ML approaches in conservation and ecological management. While we focus primarily on ecological modelling for coral reefs, our methods are generally applicable to other ecological and environmental modelling settings.

Telomere length (TL) is increasingly used in ecology as a biomarker of individual quality and environmental stress, yet research on non-model species with complex life histories remains limited. Because TL varies among tissues and across ages in a species-specific manner, identifying non-lethal tissues that reliably reflect whole-organism telomere dynamics is essential for longitudinal telomere studies in the field. This study aimed to evaluate tissue-specific TL in Japanese eel (Anguilla japonica), an endangered catadromous fish. We first mapped the chromosomal distribution of telomeric sequences using fluorescent in situ hybridization (FISH), the first application of this method in this species. We then tested whether muscle and caudal fin, which can be sampled easily and non-lethally, can serve as suitable proxy tissues for TL measurements in wild individuals. Relative telomere length (RTL) was quantified by qPCR in blood, brain, caudal fin, gonads, heart, liver, and muscle. FISH analysis confirmed telomeric repeats at all chromosomal ends, with only weak interstitial signals on three chromosomal pairs unlikely to affect qPCR-based estimates. A generalized additive mixed model and Wilcoxons signed-rank tests revealed significant inter-tissue differences: RTL was shortest in the brain and muscle and longest in liver, blood and caudal fin. Muscle and caudal fin RTL were significantly correlated with RTL in many other tissues, supporting their use as proxy tissues for longitudinal TL monitoring, including responses to environmental variation. Both total length and age were tested as explanatory variables for RTL, and the model including total length showed a better fit than the age-based model. Non-linear relationships between RTL and total length observed in several tissues suggest physiological shifts associated with growth and sexual differentiation. Overall, these findings advance understanding of telomere dynamics in eels and establish muscle and caudal fin as suitable tissues for repeated, non-lethal TL assessment in ecological and conservation contexts.

O_LIThe frequency and intensity of heat events is increasing across marine and terrestrial ecosystems. Within the same ecological community, the relative exposure and sensitivity to heat stress may vary considerably among interacting species, like predators and prey. This can be especially true for species that interact at the aquatic-terrestrial interface, as well as for interactions between primarily nocturnal and diurnal species, making it difficult to predict how such communities will respond to habitat warming. C_LIO_LIThermal limit metrics such as CTmax are often assumed to equate with ecological death because such temperatures impair behavioral activity and/or physiological functioning. Prey that are diurnally active can be more frequently exposed to temperatures that approach CTmax compared to their nocturnal predators, which may use thermal refuges during the day. Yet the impacts of daytime heat exposure on nighttime predation risk remain unknown. C_LIO_LIHere, we compared the thermal environment, performance, and heat tolerance between the predatory blue crab, Callinectus sapidus and one of its prey species, the mangrove periwinkle Littoraria anguilifera in a tropical mangrove ecosystem. We examined how exposing prey to heat stress at and below their CTmax affected their capacity to avoid predation in the field at night when predation risk is highest. C_LIO_LIWe found that acute exposure to temperatures near CTmax during the day increased the prey species susceptibility to predation during recovery at night. Although both interacting predator and prey have high thermal tolerance, prey are exposed to conditions that already reach CTmax, suggesting that current extremes in temperatures may already be influencing vulnerability to predation in this ecosystem. C_LIO_LIOur results suggest that differential exposure to sublethal heat stress in diurnal prey relative to their predator, along with the subsequent impact of these exposures on predation risk, will play a role in shaping these interacting as climate warms. C_LI

Environmental DNA (eDNA) surveys are increasingly used to assess marine biodiversity and inform deep-sea environmental decision-making, including mineral resource management and fisheries oversight. Yet standard low-volume protocols inherited from coastal work may be inadequate at depth, and no quantitative framework links depth and ecosystem context to defensible filtration volume targets. We compiled 841 eDNA samples from eight expeditions across the North Atlantic, Wider Caribbean, and Pacific (surface to 4000 m) to quantify how recoverable eDNA scales with depth and surface productivity, and to derive depth- and productivity-aware sampling targets. Total eDNA concentration declined with depth as a power law, with attenuation exponents (b) modulated by surface productivity: most gradual in eutrophic waters (b = 0.67), intermediate in mesotrophic (b = 0.90), and steepest in oligotrophic systems (b = 1.25); volume-weighted models explained 66-88% of the variance. At a fixed extract-concentration target, required filtration volumes diverged ~7-fold between oligotrophic and eutrophic systems at 200 m and ~38-fold at 4000 m. Conventional Niskin sampling, therefore, undersamples deep-sea biodiversity, particularly in mid- to low-productivity systems. Among laboratory parameters, the assay-specific extract-concentration target exerted greater leverage on required volume than extraction efficiency or elution volume. Volume-aware sampling paired with optimized recovery should be routine in deep-sea eDNA surveys.

Global changes in land use and nutrient cycling are transforming ecosystems at unprecedented rates, with significant consequences for infectious disease dynamics. Aquatic environments are particularly vulnerable because the interplay of habitat modification, nutrient enrichment, and biodiversity loss can drive pronounced changes in the community composition of food webs, including hosts and parasites. Yet, despite well-documented effects of habitat modification on aquatic communities and food webs, the mechanisms through which these changes influence infectious disease dynamics remain poorly resolved. This gap arises, in part, because it remains challenging to disentangle how multiple stressors interact to shape disease outcomes and quantify parasite levels and host densities from field-collected samples. Here, we illustrate two tools that might help address these challenges. First, highly sensitive droplet digital PCR can quantify infection loads even when the signal:noise ratio is low. Second, stepwise Bayesian path analyses can identify the direct and indirect pathways connecting land-use changes to infectious disease dynamics. As a case study, we examined cyclopoid copepods and their helminth parasite, Schistocephalus solidus, across 47 freshwater lakes on Vancouver Island, a region strongly shaped by commercial logging, including widespread clear-cutting of old-growth forests. Our results reveal a positive correlation between copepod density and deforestation, potentially mediated by associated changes in water quality and calanoid copepods, key competitors of the focal host. ddPCR enabled sensitive detection of extremely low parasite signals in field-collected copepods. We detected positive infections in only 19.5% of the lakes surveyed, highlighting the difficulty of assessing disease dynamics in natural populations. Nonetheless, this study highlights the challenges of linking land-use change to disease outcomes, while also demonstrating that sensitive molecular and statistical tools offer new ways to reveal these hidden connections.

The challenge of stratifying patients for combination therapy is both technically demanding and clinically crucial. In previous work, we introduced a multi-objective optimization framework for identifying optimally synergistic combination protocols that are robust to competing definitions of additivity. This manuscript extends this methodology to quantify how inter-individual variability in drug sensitivity influences the combination doses that optimally balance the competing objectives of synergy of efficacy and synergy of potency (a proxy measure of toxicity). For this methodology, we introduce a voxel-based stratification approach to characterize individuals (model parameterizations) into subgroups based on sensitivity to each drug as a monotherapy and in combination. As a case study, we apply the method to a preclinical dataset of murine response to the combination of an immune checkpoint inhibitor and an antiangiogenic agent. We demonstrate that the algorithm can quantify how the robustly optimal combination therapies vary across different treatment response subgroups and how the algorithm can identify subpopulations for which no meaningfully efficacious combination exists. As applying the methodology requires knowledge of specific parameter values for which measurable biomarkers may be unavailable, we also propose an initiation protocol that permits identification of the parameters necessary to place an individual in a subgroup. This methodology is a step in the direction of determining the right combination therapy for a subgroup and finding the right subgroup for an existing therapy.